Posted: December 1st, 2016

Based on the information available, briefly describe below what the linear model’s [(R^2)] and quadratic model’s [(R^2)adj] suggest about the percent variation in the dependent variable “y” that is accounted for by variation in the independent variable “x”.

Your Division’s Chief Data Analyst just left for a new career growth opportunity.  Your Division manager, realizing that some of the Division’s Educational & Training funds are being used to reimburse you for this current mathematical applications class, asks you to informally look over a set of data and to comment on the relationship between the dependent variable “y” and the independent variable “x”.  The “best fit” linear and quadratic models representing the data are shown below:

    y = 0.1828(x)2 – 92,851(x)1 + 29,950 with [(R^2)] = 0.3161 and [(R^2)adj] = 0.0881.

    y = 16.848(x)1 + 18,168 with [(R^2)] = 0.0846.

a.  Based on the information available, briefly describe below what the linear model’s [(R^2)] and quadratic model’s [(R^2)adj] suggest about the percent variation in the dependent variable “y” that is accounted for by variation in the independent variable “x”.

b.  Suppose, in this example, the dependent variable “y” represents units of a particular product sold worldwide (during one of the last 9 consecutive sales periods) and the independent variable “x” represents the number of sick days used by the sales staff during an associated sales period.  Briefly comment below about how useful the models might be based on the given data, and, if you feel the models could be improved, briefly indicate how